Field-scale Estimation of Phenotypic Parameters for Jute and Allied Fibre Crops: An Unmanned Aerial Vehicle Remote Sensing Approach

The rapid and accurate phenotypic information is key to improve agricultural production and developing strategies to reduce the impact of climate change. In the present study, the potential of unmanned aerial vehicle (UAV) based remote sensing approach was utilized in field-scale estimation of crop-specific phenotypic parameters for jute and allied crops over Central Research Institute for Jute and Allied Fibres (CRIJAF), Barrackpore, India. The UAV based multispectral images along with thermal bands were acquired during two periods, i.e., 30th May, 2023 and 11-12th July, 2023. Simultaneously, the ground-based observations on land use and crop phenotypic parameters, like leaf area index (LAI), basal diameter, plant height and leaf chlorophyll, were collected. A set of twenty-one typical UAV-based spectral indices for crop studies were computed and the same was utilized along with five multispectral channels, land surface temperature and digital surface information using a support vector machine classifier to discriminate the major land use classes (kappa ~ 0.82) and to identify the crop area for further analysis. The spectral indices were tested for collinearity and the selected indices were used for generating regression models towards the estimation of phenotypic parameters and was validated for its accuracy (normalized root mean square error 79 to 88%). The inter- & intra-plot variations in the crop phenotypic parameters were evident, which may be important inputs for improved crop management and precise estimation of crop parameters. The varying response of crop-specific phenotypic parameters during two crop stages were utilized to generate crop type maps using a maximum likelihood classifier with high accuracy (kappa ~ 0.84). Finally, the crop-specific phenotypic parameters were analysed at plot-level to study the impacts of varying environments on phenotypic expressions of jute and allied fibre crops.